scholarly journals The Camp Nou Stadium as a Testbed for City Physiology: A Modular Framework for Urban Digital Twins

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Irene Meta ◽  
Feliu Serra-Burriel ◽  
José C. Carrasco-Jiménez ◽  
Fernando M. Cucchietti ◽  
Carla Diví-Cuesta ◽  
...  
Keyword(s):  
Nonlinear Process ◽  
Point Of View ◽  
Statistical Techniques ◽  
Proof Of Concept ◽  
Agent Based ◽  
Digital Twin ◽  
Domain Specific ◽  
Digital Twins ◽  
Modular Framework

In this paper, the Camp Nou stadium is used as a testbed for City Physiology, a theoretical framework for urban digital twins. With this case study, the modularity and adaptability of the framework, originally intended for city-scale simulations, are tested on a large facility venue. As a proof of concept, several statistical techniques and an agent-based simulation platform are coupled to simulate a crowd in the stadium, and a process of four steps is followed to build the case study. Both the conceptual (interdomain) and technical (domain specific) layers of the digital twin are defined and connected in a nonlinear process so that they represent the complexity of the object to be simulated. The result obtained is a strategy to build a digital twin from the domain point of view, paving the way for more complex, more ambitious simulators.

scholarly journals Urban Digital Twins for Smart Cities and Citizens: The Case Study of Herrenberg, Germany

2020 ◽  
Vol 12 (6) ◽  
pp. 2307 ◽  
Author(s):  
Fabian Dembski ◽  
Uwe Wössner ◽  
Mike Letzgus ◽  
Michael Ruddat ◽  
Claudia Yamu
Keyword(s):  
General Public ◽  
Smart Cities ◽  
Flow Simulation ◽  
Urban Mobility ◽  
Communication Tool ◽  
Digital Twin ◽  
Collaborative Processes ◽  
Digital Twins ◽  
Collaboration And Communication

Cities are complex systems connected to economic, ecological, and demographic conditions and change. They are also characterized by diverging perceptions and interests of citizens and stakeholders. Thus, in the arena of urban planning, we are in need of approaches that are able to cope not only with urban complexity but also allow for participatory and collaborative processes to empower citizens. This to create democratic cities. Connected to the field of smart cities and citizens, we present in this paper, the prototype of an urban digital twin for the 30,000-people town of Herrenberg in Germany. Urban digital twins are sophisticated data models allowing for collaborative processes. The herein presented prototype comprises (1) a 3D model of the built environment, (2) a street network model using the theory and method of space syntax, (3) an urban mobility simulation, (4) a wind flow simulation, and (5) a number of empirical quantitative and qualitative data using volunteered geographic information (VGI). In addition, the urban digital twin was implemented in a visualization platform for virtual reality and was presented to the general public during diverse public participatory processes, as well as in the framework of the “Morgenstadt Werkstatt” (Tomorrow’s Cities Workshop). The results of a survey indicated that this method and technology could significantly aid in participatory and collaborative processes. Further understanding of how urban digital twins support urban planners, urban designers, and the general public as a collaboration and communication tool and for decision support allows us to be more intentional when creating smart cities and sustainable cities with the help of digital twins. We conclude the paper with a discussion of the presented results and further research directions.

The Digital Transformation of the Product Management Process: Conception of Digital Twin Impacts for the Different Stages

2019 ◽  
Vol 5 (2) ◽  
pp. 74-86 ◽  
Author(s):  
Günter Hofbauer ◽  
Anita Sangl ◽  
Sonja Engelhardt
Keyword(s):  
Digital Transformation ◽  
Point Of View ◽  
Product Management ◽  
Extensive Literature ◽  
Management Process ◽  
Digital Twin ◽  
Digital Twins ◽  
Analytical Point ◽  
Potential Benefits ◽  
Process Conception

In this paper the potential impact of digital transformation in general and digital twin applications on the Product Management Process (PMP) in particular will be investigated. The object is to figure out the potential benefits of digital twin utilization. Methodologically, a conceptual and analytical approach are applied in using statistical data, surveys, latest literature and logical conclusions. Thus, the approach is twofold: from the conceptual point of view the different types of digital twins are introduced; from the analytical point of view different applications in different stages of the PMP will be subject to investigation. So, this paper can be categorized as conceptual paper based on an extensive literature research. The findings of research revealed that the digital transformation can offer various benefits for the PMP. It can be summarized that in all phases of the PMP potential benefits can be identified. The most important is saving time and money, avoiding waste of physical resources and simultaneously raising quality, reliability and competitive advantage. Regarding the originality value it can be stated that this is the first comprehensive examination of the entire PMP with regard to digital transformation in order to identify sources of potential benefits.

scholarly journals When Digital Twin Meets Network Softwarization in the Industrial IoT: Real-Time Requirements Case Study

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8194
Author(s):  
Mehdi Kherbache ◽  
Moufida Maimour ◽  
Eric Rondeau
Keyword(s):  
Real Time ◽  
Industrial Systems ◽  
Digital Twin ◽  
Digital Twins ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Time Requirements ◽  
Loop Network ◽  
Sdn Controller

The Industrial Internet of Things (IIoT) is known to be a complex system because of its severe constraints as it controls critical applications. It is difficult to manage such networks and keep control of all the variables impacting their operation during their whole lifecycle. Meanwhile, Digital Twinning technology has been increasingly used to optimize the performances of industrial systems and has been ranked as one of the top ten most promising technological trends in the next decade. Many Digital Twins of industrial systems exist nowadays but only few are destined to networks. In this paper, we propose a holistic digital twinning architecture for the IIoT where the network is integrated along with the other industrial components of the system. To do so, the concept of Network Digital Twin is introduced. The main motivation is to permit a closed-loop network management across the whole network lifecycle, from the design to the service phase. Our architecture leverages the Software Defined Networking (SDN) paradigm as an expression of network softwarization. Mainly, the SDN controller allows for setting up the connection between each Digital Twin of the industrial system and its physical counterpart. We validate the feasibility of the proposed architecture in the process of choosing the most suitable communication mechanism that satisfies the real-time requirements of a Flexible Production System.

scholarly journals A Generic Asset Model for Implementing Product Digital Twins in Smart Remanufacturing

2021 ◽  
Author(s):  
Mairi Kerin ◽  
Duc Truong Pham ◽  
Jun Huang ◽  
Jeremy Hadall
Keyword(s):  
Real Time ◽  
Manufacturing Industry ◽  
Integrated System ◽  
Embedded Sensors ◽  
Functional Requirements ◽  
Digital Twin ◽  
Digital Twins ◽  
The Impact ◽  
The Internet Of Things

Abstract A digital twin is a “live” virtual replica of a sensorised component, product, process, human, or system. It accurately copies the entity being modelled by capturing information in real time or near real time from the entity through embedded sensors and the Internet-of-Things. Many applications of digital twins in manufacturing industry have been investigated. This article focuses on the development of product digital twins to reduce the impact of quantity, quality, and demand uncertainties in remanufacturing. Starting from issues specific to remanufacturing, the article derives the functional requirements for a product digital twin for remanufacturing and proposes a UML model of a generic asset to be remanufactured. The model has been demonstrated in a case study which highlights the need to translate existing knowledge and data into an integrated system to realise a product digital twin, capable of supporting remanufacturing process planning.

scholarly journals On Digital Twin Condition Monitoring Approach for Drivetrains in Marine Applications

2019 ◽  
Author(s):  
Sigrid S. Johansen ◽  
Amir R. Nejad
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Offshore Wind ◽  
Test Rig ◽  
Digital Twin ◽  
Model Based ◽  
Twin Model ◽  
Digital Twins ◽  
Fidelity Model

Abstract A digital twin is a virtual representation of a system containing all information available on site. This paper presents condition monitoring of drivetrains in marine power transmission systems through digital twin approach. A literature review regarding current operations concerning maintenance approaches in todays practices are covered. State-of-the-art fault detection in drivetrains is discussed, founded in condition monitoring, data-based schemes and model-based approaches, and the digital twin approach is introduced. It is debated that a model-based approach utilizing a digital twin could be recommended for fault detection of drivetrains. By employing a digital twin, fault detection would be extended to relatively highly diagnostic and predictive maintenance programme, and operation and maintenance costs could be reduced. A holistic model system approach is considered, and methodologies of digital twin design are covered. A physical-based model rather than a data based model is considered, however there are no clear answer whereas which type is beneficial. That case is mostly answered by the amount of data available. Designing the model introduces several pitfalls depending on the relevant system, and the advantages, disadvantages and appropriate applications are discussed. For a drivetrain it is found that multi-body simulation is advised for the creation of a digital twin model. A digital twin of a simple drivetrain test rig is made, and different modelling approaches were implemented to investigate levels of accuracy. Reference values were derived empirically by attaching sensors to the drivetrain during operation in the test rig. Modelling with a low fidelity model showed high accuracy, however it would lack several modules required for it to be called a digital twin. The higher fidelity model showed that finding the stiffness parameter proves challenging, due to high stiffness sensitivity as the experimental modelling demonstrates. Two industries that could have significant benefits from implementing digital twins are discussed; the offshore wind industry and shipping. Both have valuable assets, with reliability sensitive systems and high costs of downtime and maintenance. Regarding the shipping industry an industrial case study is done. Area of extra focus is operations of Ro-Ro (roll on-roll off) vessels. The vessels in the case study are managed by Wilhelmsen Ship Management and a discussion of the implementation of digital twins in this sector is comprised in this article.

scholarly journals A digital twin framework for improving energy efficiency and occupant comfort in public and commercial buildings

2021 ◽  
Vol 4 (S2) ◽  
Author(s):  
Anders Clausen ◽  
Krzysztof Arendt ◽  
Aslak Johansen ◽  
Fisayo Caleb Sangogboye ◽  
Mikkel Baun Kjærgaard ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Controlled Environment ◽  
Building Automation ◽  
Digital Twin ◽  
Digital Twins ◽  
Occupant Comfort

AbstractModel Predictive Control (MPC) can be used in the context of building automation to improve energy efficiency and occupant comfort.Ideally, the MPC algorithm should consider current- and planned usage of the controlled environment along with initial state and weather forecast to plan for optimal comfort and energy efficiency.This implies the need for an MPC application which 1) considers multiple objectives, 2) can draw on multiple data sources, and 3) provides an approach to effectively integrate against heterogeneous building automation systems to make the approach reusable across different installations.To this end, this paper presents a design and implementation of a framework for digital twins for buildings in which the controlled environments are represented as digital entities. In this framework, digital twins constitute parametrized models which are integrated into a generic control algorithm that uses data on weather forecasts, current- and planned occupancy as well as the current state of the controlled environment to perform MPC. This data is accessed through a generic data layer to enable uniform data access. This enables the framework to switch seamlessly between simulation and real-life applications and reduces the barrier towards reusing the application in a different control environment.We demonstrate an application of the digital twin framework on a case study at the University of Southern Denmark where a digital twin has been used to control heating and ventilation.From the case study, we observe that we can switch from rule-based control to model predictive control with no immediate adverse effects towards comfort or energy consumption. We also identify the potential for an increase in energy efficiency, as well as introduce the possibility of planning energy consumption against local electricity production or market conditions, while maintaining occupant comfort.

Life.course digital T.wins – I.ntelligent M.onitoring for E.arly and continuous intervention and prevention (LifeTIME): Proposal for a proof-of-concept study (Preprint)

2021 ◽  
Author(s):  
Madison Milne-Ives ◽  
Lorna Fraser ◽  
Asiya Khan ◽  
David Walker ◽  
Michelle Helena van Velthoven ◽  
...  
Keyword(s):  
Risk Factors ◽  
Life Course ◽  
Data Science ◽  
Healthcare Systems ◽  
Health Conditions ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
Proof Of Concept ◽  
Digital Twin ◽  
Digital Twins

BACKGROUND Multimorbidity, which is associated with significant negative outcomes for individuals and healthcare systems, is increasing in the UK. However, there is a lack of knowledge about the risk factors (including health, behaviour, and environment) for multimorbidity over time. An interdisciplinary approach is essential, as data science, artificial intelligence, and concepts from engineering (digital twins), have the potential to enable personalised simulation of life-course risk for the development of multimorbidity by identifying key risk factors throughout the life course. Predicting the risk of developing clusters of health conditions before they occur would add clinical value by enabling targeted early preventive interventions, advancing personalised care to improve outcomes, and reducing the burden on the UK’s healthcare systems. OBJECTIVE This study aims to identify key risk factors that predict multimorbidity throughout the lifetime through the development of an intelligent agent using digital twins so that early interventions can be delivered to improve health outcomes. The objectives of this study are to identify key predictors of lifetime risk of multimorbidity, create a series of simulated computational digital twins that predict levels of risk for specific clusters of factors, and test the feasibility of the system. METHODS This study will use machine learning to identify key risk factors throughout life that predict the risk of later multimorbidity to develop digital twins. The first stage of the development will be the training of a base predictive model. Data from the National Child Development Study (NCDS), the North West London Integrated Care Record (NWL ICR), the Clinical Practice Research Datalink (CPRD), and Cerner's Real World Data will be split into subsets for training and validation, which will be done following the k-fold cross-validation procedure and assessed with the PROBAST risk of bias tool. Two additional datasets - from the early-LIfe data cross-LInkage in Research (eLIXIR) study and the Children and Young People’s Health Partnership (CYPHP) randomised controlled trial - will be used in addition to the model to develop a series of digital twin personas that simulate clusters of factors that predict different levels of risk of developing multimorbidity. RESULTS The expected results are a validated model, a series of digital twin personas, and an assessment of proof-of-concept. CONCLUSIONS Digital twins could provide an individualised early warning system that predicts the risk of future health conditions and recommends the intervention that is most likely to be effective at minimising that risk. These insights could have a significant positive impact on an individual’s quality of life and healthy life expectancy and reduce population-level health burdens.

scholarly journals Accelerating Biologics Manufacturing by Modeling or: Is Approval under the QbD and PAT Approaches Demanded by Authorities Acceptable Without a Digital-Twin?

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 94 ◽  
Author(s):  
Steffen Zobel-Roos ◽  
Axel Schmidt ◽  
Fabian Mestmäcker ◽  
Mourad Mouellef ◽  
Maximilian Huter ◽  
...  
Keyword(s):  
Monoclonal Antibodies ◽  
Process Development ◽  
Process Analytical Technology ◽  
Control Strategies ◽  
Development Stage ◽  
Point Of View ◽  
Digital Twin ◽  
Market Competitiveness ◽  
Digital Twins ◽  
Potential Methods

Innovative biologics, including cell therapeutics, virus-like particles, exosomes,recombinant proteins, and peptides, seem likely to substitute monoclonal antibodies as the maintherapeutic entities in manufacturing over the next decades. This molecular variety causes agrowing need for a general change of methods as well as mindset in the process development stage,as there are no platform processes available such as those for monoclonal antibodies. Moreover,market competitiveness demands hyper-intensified processes, including accelerated decisionstoward batch or continuous operation of dedicated modular plant concepts. This indicates gaps inprocess comprehension, when operation windows need to be run at the edges of optimization. Inthis editorial, the authors review and assess potential methods and begin discussing possiblesolutions throughout the workflow, from process development through piloting to manufacturingoperation from their point of view and experience. Especially, the state-of-the-art for modeling inred biotechnology is assessed, clarifying differences and applications of statistical, rigorousphysical-chemical based models as well as cost modeling. “Digital-twins” are described and effortsvs. benefits for new applications exemplified, including the regulation-demanded QbD (quality bydesign) and PAT (process analytical technology) approaches towards digitalization or industry 4.0based on advanced process control strategies. Finally, an analysis of the obstacles and possiblesolutions for any successful and efficient industrialization of innovative methods from processdevelopment, through piloting to manufacturing, results in some recommendations. A centralquestion therefore requires attention: Considering that QbD and PAT have been required byauthorities since 2004, can any biologic manufacturing process be approved by the regulatoryagencies without being modeled by a “digital-twin” as part of the filing documentation?

scholarly journals Modelling for Digital Twins—Potential Role of Surrogate Models

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 476
Author(s):  
Ágnes Bárkányi ◽  
Tibor Chován ◽  
Sándor Németh ◽  
János Abonyi
Keyword(s):  
Model Building ◽  
Surrogate Models ◽  
Uncertain Information ◽  
Industrial Case Study ◽  
Continuous Processes ◽  
Digital Twin ◽  
Box Models ◽  
Digital Twins

The application of white box models in digital twins is often hindered by missing knowledge, uncertain information and computational difficulties. Our aim was to overview the difficulties and challenges regarding the modelling aspects of digital twin applications and to explore the fields where surrogate models can be utilised advantageously. In this sense, the paper discusses what types of surrogate models are suitable for different practical problems as well as introduces the appropriate techniques for building and using these models. A number of examples of digital twin applications from both continuous processes and discrete manufacturing are presented to underline the potentials of utilising surrogate models. The surrogate models and model-building methods are categorised according to the area of applications. The importance of keeping these models up to date through their whole model life cycle is also highlighted. An industrial case study is also presented to demonstrate the applicability of the concept.

scholarly journals Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
D. J. Wagg ◽  
K. Worden ◽  
R. J. Barthorpe ◽  
P. Gardner
Keyword(s):  
Asset Management ◽  
State Of The Art ◽  
Industrial Applications ◽  
Transport Systems ◽  
Synthesis Process ◽  
Small Scale ◽  
Mathematical Framework ◽  
Digital Twin ◽  
Digital Twins

Abstract This paper presents a review of the state of the art for digital twins in the application domain of engineering dynamics. The focus on applications in dynamics is because: (i) they offer some of the most challenging aspects of creating an effective digital twin, and (ii) they are relevant to important industrial applications such as energy generation and transport systems. The history of the digital twin is discussed first, along with a review of the associated literature; the process of synthesizing a digital twin is then considered, including definition of the aims and objectives of the digital twin. An example of the asset management phase for a wind turbine is included in order to demonstrate how the synthesis process might be applied in practice. In order to illustrate modeling issues arising in the construction of a digital twin, a detailed case study is presented, based on a physical twin, which is a small-scale three-story structure. This case study shows the progression toward a digital twin highlighting key processes including system identification, data-augmented modeling, and verification and validation. Finally, a discussion of some open research problems and technological challenges is given, including workflow, joints, uncertainty management, and the quantification of trust. In a companion paper, as part of this special issue, a mathematical framework for digital twin applications is developed, and together the authors believe this represents a firm framework for developing digital twin applications in the area of engineering dynamics.

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